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Record W4417252450 · doi:10.1051/0004-6361/202556371

Resolution and calibration effects in high contrast polarimetric imaging of circumstellar scattering regions

2025· article· en· W4417252450 on OpenAlexaff
H. M. Schmid, Jie Ma

Bibliographic record

VenueAstronomy and Astrophysics · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstrophysics and Star Formation Studies
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsPolarimetryScatteringCalibrationStokes parametersPolarization (electrochemistry)Point spread functionConvolution (computer science)Deconvolution

Abstract

fetched live from OpenAlex

Context . Many circumstellar dust scattering regions have been detected and investigated with polarimetric imaging. However, the quantitative determination of the intrinsic polarization and of dust properties is difficult because of complex observational effects. Aims . This work investigates the instrumental convolution and polarimetric calibration effects for high contrast imaging polarimetry with the aim of defining the measuring parameters and calibration procedures for accurate measurements of the circumstellar polarization. Methods . We simulated the instrumental convolution and polarimetric cancellation effects for two axisymmetric point spread functions (PSFs), a Gaussian PSF G and an extended PSF AO , typical for a modern adaptive optics system. The PSFs have the same diameter D PSF for the PSF peak. Further, polarimetric zero-point corrections (zp-corrections) were simulated for different cases, including coronagraphic observations and systems with barely resolved circumstellar scattering regions. Results . The PSF convolution reduces the integrated azimuthal polarization, Σ Q ϕ , for the scattering region, while the net Stokes signals Σ Q and Σ U are not changed. For non-axisymmetric systems, a spurious U ϕ signal is introduced by the convolution. These effects are strong for compact systems and for the convolution with an extended PSF AO . Compact scattering regions can be detected down to an inner working angle of r ≈ D PSF based on the presence of a net Σ Q ϕ signal. Unresolved central scattering regions can introduce a central Stokes Q, U signal that can be used to constrain the scattering geometry even at separations r < D PSF . The smearing by the halo of the PSF AO produces an extended, low surface brightness polarization signal. These effects change the angular distribution of the azimuthal polarization, Q ϕ ( ϕ ), but the initial Q ϕ ′ ( ϕ ) signal can be partly recovered with the analysis of measured Stokes Q and U quadrant pattern. We find that applying a polarimetric zp-correction for the removal of offsets from instrumental or interstellar polarization depends on the selected reference region and can introduce strong bias effects for Σ Q and Σ U and the azimuthal distribution of Q ϕ ( ϕ ). Strategies for the zp-correction are described for different data types, such as coronagraphic data or observations of partly unresolved systems. These procedures provide polarization parameters that can be easily reproduced with model simulations. Conclusions . The simulations describe the impact of the PSF convolution and of calibration offsets for imaging polarimetry in a systematic way, and they show when these effects are strong and how they can be considered in the analysis. This defines also suitable measuring parameters and procedures for the quantitative characterization of the intrinsic scattering polarization Q ϕ ′ for an accurate determination of the properties of the circumstellar dust.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.203
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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